We present GaussianAvatar an efficient approach to creating realistic human avatars with
dynamic 3D appearances from a single video. We start by introducing animatable 3D …

Recent advances in neural rendering have improved both training and rendering times by
orders of magnitude. While these methods demonstrate state-of-the-art quality and speed …

Realistic 3D human generation from text prompts is a desirable yet challenging task.
Existing methods optimize 3D representations like mesh or neural fields via score distillation …

Abstract We introduce Gaussian Articulated Template Model (GART) an explicit efficient and
expressive representation for non-rigid articulated subject capturing and rendering from …

We introduce an approach that creates animatable human avatars from monocular videos
using 3D Gaussian Splatting (3DGS). Existing methods based on neural radiance fields …

Reconstructing dynamic objects from monocular videos is a severely underconstrained and
challenging problem and recent work has approached it in various directions. However …

We present DreamWaltz, a novel framework for generating and animating complex 3D
avatars given text guidance and parametric human body prior. While recent methods have …

Realistic human-centric rendering plays a key role in both computer vision and computer
graphics. Rapid progress has been made in the algorithm aspect over the years, yet existing …

This work addresses the problem of real-time rendering of photorealistic human body
avatars learned from multi-view videos. While the classical approaches to model and render …

We present SplattingAvatar a hybrid 3D representation of photorealistic human avatars with
Gaussian Splatting embedded on a triangle mesh which renders over 300 FPS on a modern …